Opinion filtered recommendation trust model in peer-to-peer networks

Weihua Song, Vir V. Phoha

Research output: Chapter in Book/Entry/PoemConference contribution

2 Scopus citations


A multiagent distributed system consists of a network of heterogeneous peers of different trust evaluation standards. A major concern is how to form a requester's own trust opinion of an unknown party from multiple recommendations, and how to detect deceptions since recommenders may exaggerate their ratings. This paper presents a novel application of neural networks in deriving personalized trust opinion from heterogeneous recommendations. The experimental results showed that a three-layered neural network converges at an average of 12528 iterations and 93.75% of the estimation errors are less than 5%. More important, the model is adaptive to trust behavior changes and has robust performance when there is high estimation accuracy requirement or when there are deceptive recommendations.

Original languageEnglish (US)
Title of host publicationAgents and Peer-to-Peer Computing - Third International Workshop, AP2PC 2004, Revised and Invited Papers
PublisherSpringer Verlag
Number of pages8
ISBN (Print)3540297553, 9783540297550
StatePublished - 2005
Externally publishedYes
EventThird International Workshop on Agents and Peer-to-Peer Computing, AP2PC 2004 - New York, NY, United States
Duration: Jul 19 2004Jul 19 2004

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3601 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


OtherThird International Workshop on Agents and Peer-to-Peer Computing, AP2PC 2004
Country/TerritoryUnited States
CityNew York, NY

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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